Book contents
- Research Methods and Applied Statistics
- Reviews
- Research Methods and Applied Statistics
- Copyright page
- Dedication
- Contents
- Guided Tour
- Preface
- Acknowledgments
- 1 Developing a Research Study Proposal
- 2 Developing a Research Question and Hypotheses, Choosing Statistics, and Estimating the Sample Size
- 3 Experimental vs. Correlational Studies, Measuring Constructs, and Internal Consistency Reliability
- 4 Demographics, Creating Surveys, and Data Management
- 5 Qualitative and Mixed-Methods Approaches
- 6 Beginning Your Analysis: Descriptive Statistics and Correlations
- 7 Relationships Between Nominal Data: Chi-Square and McNemar’s Tests
- 8 Comparing Means with Two Groups: The t and U Tests
- 9 Comparing Means with Multiple Groups: The Analysis of Variance (ANOVA)
- 10 Multiple Regression Analysis: Predicting a Continuous Variable
- 11 Binary Logistic Regression Analysis: Predicting a Dichotomous Variable
- 12 Data Visualization and Interpretation
- 13 Pulling it All Together: The Research Paper, the Research Poster, and Everything
- Appendix A Installing R and Required Libraries
- Further Reading
- Index
2 - Developing a Research Question and Hypotheses, Choosing Statistics, and Estimating the Sample Size
Published online by Cambridge University Press: 17 December 2025
Book contents
- Research Methods and Applied Statistics
- Reviews
- Research Methods and Applied Statistics
- Copyright page
- Dedication
- Contents
- Guided Tour
- Preface
- Acknowledgments
- 1 Developing a Research Study Proposal
- 2 Developing a Research Question and Hypotheses, Choosing Statistics, and Estimating the Sample Size
- 3 Experimental vs. Correlational Studies, Measuring Constructs, and Internal Consistency Reliability
- 4 Demographics, Creating Surveys, and Data Management
- 5 Qualitative and Mixed-Methods Approaches
- 6 Beginning Your Analysis: Descriptive Statistics and Correlations
- 7 Relationships Between Nominal Data: Chi-Square and McNemar’s Tests
- 8 Comparing Means with Two Groups: The t and U Tests
- 9 Comparing Means with Multiple Groups: The Analysis of Variance (ANOVA)
- 10 Multiple Regression Analysis: Predicting a Continuous Variable
- 11 Binary Logistic Regression Analysis: Predicting a Dichotomous Variable
- 12 Data Visualization and Interpretation
- 13 Pulling it All Together: The Research Paper, the Research Poster, and Everything
- Appendix A Installing R and Required Libraries
- Further Reading
- Index
Summary
Often, students generate a research question, formulate hypotheses, and wonder, “What statistics should I use?” These statistics, drilled into their brains from previous courses, sometimes contain little to no meaningful associations to real-world concepts. It is the transference of these skills (or lack of!) that can hang up a new researcher on how to explore their hypotheses. This chapter brings students through the process of selecting successful research questions and the formulation of hypotheses. Dependent and independent variables are reviewed along with cause-and-effect relationships. The relationship between statistical power, statistical significance, effect size, and sample size is discussed along with step-by-step instructions for estimating sample size.
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- Research Methods and Applied StatisticsA Practical Guide to Conducting Research, pp. 32 - 69Publisher: Cambridge University PressPrint publication year: 2025
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